Statistics
5302, Spring 2011
APPLIED REGRESSION ANALYSIS
Course
Instructor: R. D. Cook, 397
Ford Hall, Minneapolis (5-7732). Email: dennis@stat.umn.edu.
Office Hours: 2:15-3:00 MW and by appointment.
Lab
Instructor: Jie Ren. Email: jren@stat.umn.edu.
Office Hours: TBA
Lectures:
1:25-2:15 MWF, 110 Ford Hall.
Labs: (1) 2:30-3:20, (2) 3:35-4:25 on Thursdays Vincent
Hall 301. During the regular lab sessions, you will go over assignments,
receive instruction to supplement the lectures and have an opportunity for
questions.
Text:
Cook R D and Weisberg S (1999). Applied
Regression Including Computing and Graphics. New York: Wiley. The web
site for the text is at http://www.stat.umn.edu/arc. There you will find
background information that may be helpful during the semester, and the
computer program Arc that was
written to accompany the text. This text is required.
Computing:
The computer program Arc is an integral part of this course. Information on the
use of Arc is included in the
text. You will receive further
instruction on Arc during both
labs and lectures. All data sets discussed in the text and almost all data sets
to be used in the course come with Arc. Instructions on how to gain access to Arc in computer labs, and on how to load it onto your own
computer will be discussed in your first lab session on Thursday, January 20.
You must be familiar with Arc as soon as possible. You will also need a hand calculator that can find
roots, logs and exponentials. Bring your calculator to the exams.
Homework: Homework is a required part of the course. There
will be 10-12 assignments during the semester. Portions of all assignments will
be graded and most will require computer work. No late homework will be
accepted unless prior permission has been obtained from the instructor or the
teaching assistant. Usually, assignments will be given in class on Wednesdays
and will be due in lab on the Thursday of the following week. You are required
to hand in only the problems to be graded, but you should do all of the
problems assigned to keep up with the material and prepare for the exams. You
are permitted to discuss homework problems with others in the class, but the
work turned in must be your own.
Conscientious completion of all homework assignments is essential to getting a
good grade in this course (see grading below).
Exams: There will be two in-class exams plus the
final. The tentative dates for the
in-class exams are February 25 and April 8. The exact date will be announced at
least one week prior to the exam. The final is scheduled for 1:30 – 3:30
am, Wednesday, May 13. You could be required to do computer analyses to prepare
for exams, and the final may have a take-home portion.
Grading:
Homework 40%; 1st Exam 15%; 2nd Exam
20%; Final Exam 25%. As a rough
guide based on past classes you can expect that about 90% will be required for
an "A", between 76% and 90% will be required for a "B",
between 65% and 76% for a "C", although the exact percentages will
vary depending on the difficulty of the homework and exams. A grade of
"S" requires a clear demonstration of knowledge of the subject matter
and a passing grade on the final exam. For example, satisfactory performance on
8 assignments, one in-class exam and the final exam would be sufficient.
Makeup exams will be given only for documented reasons outside your control,
e.g. illness supported by a letter from your doctor. Social and vacation
conflicts are not acceptable reasons.
Incompletes: A grade of "I" will be given only in
extraordinary circumstances, and then only by written agreement between the
instructor and the student. An incomplete will not be given on the grounds of
an unexpectedly heavy course load. Students wishing to make up a
prior incomplete must obtain permission from the instructor in advance.
Handouts: Copies of handouts will be available on the
course Web page at www.stat.umn.edu/~dennis/5302S11. (Note that the S is
uppercase)
Coverage:
The table of contents for the text is
the course outline. We will cover Chapters 1-15, 21, 22 and, time permitting, a
little nonlinear regression. While the emphasis given during lecture will be a
good indication of relative importance, you will be responsible for all the
material in assigned readings.
Chapter
1 is largely review and you are expected to be familiar with the statistical
material contained therein. This chapter is intended to provide some review,
introduce some of the notation used in the course, and provide instruction on
the use of Arc in a familiar
statistical context. Chapters 2 and 3 introduce a few fundamental ideas of
regression. Chapters 1- 3 will be covered rapidly. The pace of the course in
chapters covered per lecture will begin to slow when we reach Chapter 4, but
the material covered per lecture will be relatively constant. Some of the
chapters will be covered in Lab.
-----------------------------------------------------
DISABILITY ACCESS STATEMENT
This material is available in alternative formats upon
request. Please contact the secretarial staff of the School of Statistics, 313
Ford Hall, 625-7030.
------------------------------------------------------